fbpx

Miloลก ลฝivadinoviฤ‡ – Faculty of Organizational Sciences, Jove Iliฤ‡a 54, 11000 Belgrade, Republic of Serbia

Keywords:
LLM;
Algorithm coding tests;
Recruitment

DOI: https://doi.org/10.31410/LIMEN.S.P.2023.21

Abstract: Usage of programming interview questions which consist of codยญing is one of the most common approaches when hiring new candidates. Candidates should possess a variety of skills and knowledge in order to solve these assignments properly within the time and memory constraints in order to pass the examinations. With the advent of LLM (Large Language Models) architectures such as ChatGPT, we are able to prove that the most common interview questions are trivial as a measure of knowledge. By comparing a dataset of common programming interview questions with answers generยญated by ChatGPT, we have shown significant results in favor of ChatGPT as a solution for solving programming interview questions with an acceptance rate of 96.58% which is 46.45% higher than the average. We conclude from these results that the existing practice of programming interview questions is flawed and that significant changes should be made to render it relevant or to abandon it completely in candidate testing.

Download file

LIMEN Conference

9th International Scientific-Business Conference – LIMEN 2023 – Leadership, Innovation, Management and Economics: Integrated Politics of Research – SELECTED PAPERS, Hybrid (Graz University of Technology, Graz, Austria), December 7, 2023

LIMEN Selected papers published by the Association of Economists and Managers of the Balkans, Belgrade, Serbia

LIMEN Conference 2023 Selected papers: ISBN 978-86-80194-79-0, ISSN 2683-6149, DOI: https://doi.org/10.31410/LIMEN.S.P.2023

Creative Commons Nonย Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission.ย 

Suggested citation

ลฝivadinoviฤ‡, M. (2023). Application of LLMs for Solving Algorithm Coding Tests in Recruitment. In V. Bevanda (Ed.), International Scientific-Business Conference – LIMEN 2023: Vol 9. Selected papers (pp. 21-27). Association of Economists and Managers of the Balkans. https://doi.org/10.31410/LIMEN.S.P.2023.21

References

Adamopoulou, E., & Moussiades, L. (2020). An Overview of Chatbot Technology. Artificial Intelligence Applications and Innovations, 584, 373โ€“383. https://doi.org/10.1007/978-3-030-49186-4_31

Arefin, S., Heya, T., Al-Qudah, H., Ineza, Y., & Serwadda, A. (2023). Unmasking the Giant: A Comprehensive Evaluation of ChatGPTโ€™s Proficiency in Coding Algorithms and Data Strucยญtures. Proceedings of the 16th International Conference on Agents and Artificial Intelligence. https://doi.org/10.5220/0012467100003636

Barat, M., Soyer, P., & Dohan, A. (2023). Appropriateness of Recommendations Provided by ChatGPT to Interventional Radiologists. Canadian Association of Radiologists Journal, 74(4), 758-763. https://doi.org/10.1177/08465371231170133

Basic Calculator II. (n.d.). In LeetCode. https://leetcode.com/problems/basic-calculator-ii/descriptionย 

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., โ€ฆ Amodei, D. (2020). Language Models are Few-Shot Learners (arXiv:2005.14165). arXiv. https://doi.org/10.48550/arXiv.2005.14165ย 

ChatGPT. (n.d.). https://chat.openai.comย 

Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. de O., Kaplan, J., Edwards, H., Burda, Y., Joยญseph, N., Brockman, G., Ray, A., Puri, R., Krueger, G., Petrov, M., Khlaaf, H., Sastry, G., Mishkin, P., Chan, B., Gray, S., โ€ฆ Zaremba, W. (2021). Evaluating Large Language Models Trained on Code (arXiv:2107.03374). arXiv. http://arxiv.org/abs/2107.03374ย 

Dahlkemper, M. N., Lahme, S. Z., & Klein, P. (2023). How do physics students evaluate artificial intelligence responses on comprehension questions? A study on the perceived scientific accuยญracy and linguistic quality of ChatGPT. Physical Review Physics Education Research, 19(1). https://doi.org/10.1103/physrevphyseducres.19.010142ย 

Divide Two Integers. (n.d.). In LeetCode. https://leetcode.com/problems/divide-two-integers/descriptionย 

Dong, Y., Jiang, X., Jin, Z., & Li, G. (2023). Self-collaboration Code Generation via ChatGPT (arXยญiv:2304.07590). arXiv. http://arxiv.org/abs/2304.07590ย 

Gilardi, F., Alizadeh, M., & Kubli, M. (2023). ChatGPT outperforms crowd workers for text-annotaยญtion tasks. Proceedings of the National Academy of Sciences, 120(30). https://doi.org/10.1073/pnas.2305016120ย 

GitHub Copilot Your AI pair programmer. (n.d.). In GitHub. https://github.com/features/copilotย 

HackerRank – Online Coding Tests and Technical Interviews. (n.d.). In HackerRank. https://www.hackerrank.com/ย 

Kamal, U., Tonmoy, T. I., Das, S., & Hasan, M. K. (2020). Automatic Traffic Sign Detection and Recognition Using SegU-Net and a Modified Tversky Loss Function With L1-Constraint. IEEE Transactions on Intelligent Transportation Systems, 21(4), 1467โ€“1479. https://doi.org/10.1109/TITS.2019.2911727ย 

LeetCode – The Worldโ€™s Leading Online Programming Learning Platform. (n.d.). https://leetcode.com/ย 

Li, P. L., Ko, A. J., & Zhu, J. (2015). What Makes a Great Software Engineer? 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering. https://doi.org/10.1109/icse.2015.335ย 

Ling, M. H. (2023). ChatGPT (Feb 13 Version) is a Chinese Room. https://doi.org/10.48550/ARXIV.2304.12411ย 

Liu, K., Han, Y., Zhang, J. M., Chen, Z., Sarro, F., Harman, M., Huang, G., & Ma, Y. (2023). Who Judges the Judge: An Empirical Study on Online Judge Tests. Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis. https://doi.org/10.1145/3597926.3598060ย 

Liu, Y., Le-Cong, T., Widyasari, R., Tantithamthavorn, C., Li, L., Le, X.-B. D., & Lo, D. (2023). Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues. https://doi.org/10.48550/ARXIV.2307.12596ย 

Mastropaolo, A., Pascarella, L., Guglielmi, E., Ciniselli, M., Scalabrino, S., Oliveto, R., & Bavoยญta, G. (2023). On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot (arXiv:2302.00438). arXiv. http://arxiv.org/abs/2302.00438ย 

Moradi Dakhel, A., Majdinasab, V., Nikanjam, A., Khomh, F., Desmarais, M. C., & Jiang, Z. M. J. (2023). GitHub Copilot AI pair programmer: Asset or Liability? Journal of Systems and Softยญware, 203, 111734. https://doi.org/10.1016/j.jss.2023.111734ย 

OpenAI. (2023). GPT-4 Technical Report (arXiv:2303.08774). arXiv. http://arxiv.org/abs/2303.08774ย 

Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (n.d.). Language Models are Unsupervised Multitask Learners.

Shone, J. (2022). Yes, You Can Make an App Too: A Systematic Study of Prompt Engineering in the Automatic Generation of Mobile Applications from User Queries.

The Skyline Problem. (n.d.). In LeetCode. https://leetcode.com/problems/the-skyline-problem/descriptionย ย 

Sorensen, T., Robinson, J., Rytting, C., Shaw, A., Rogers, K., Delorey, A., Khalil, M., Fulda, N., & Wingate, D. (2022). An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels. Proceedings of the 60th Annual Meeting of the Association for Comยญputational Linguistics (Volume 1: Long Papers). https://doi.org/10.18653/v1/2022.acl-long.60ย 

TopKFrequentElements.(n.d.). InLeetCode. https://leetcode.com/problems/top-k-frequent-elements/descriptionย 

Top Interview Questions. (n.d.). In LeetCode. https://leetcode.com/problem-list/top-interview-questions/ย 

Touvron, H., Martin, L., & Stone, K. (n.d.). Llama 2: Open Foundation and Fine-Tuned Chat Models.

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosยญukhin, I. (2023). Attention Is All You Need (arXiv:1706.03762). arXiv. https://doi.org/10.48550/arXiv.1706.03762ย 

Wiggle Sort II. (n.d.). In LeetCode. https://leetcode.com/problems/wiggle-sort-ii/descriptionย 

Witteveen, S., & Andrews, M. (2022). Investigating Prompt Engineering in Diffusion Models. Corยญnell University – arXiv. https://doi.org/10.48550/arxiv.2211.15462ย 

Connect with us

Association of Economists and Managers of the Balkans โ€“ UdEkoM Balkan
179 Ustanicka St, 11000 Belgrade, Republic of Serbia

https://www.udekom.org.rs/home

Udekom Balkans isย a dynamic non-governmental and non-profit organization, established in 2014 with a mission to foster the growth of scientific knowledge within the Balkan region and beyond. Our primary objectives include advancing the fields of management and economics, as well as providing educational resources to our members and the wider public.

Who We Are: Our members include esteemed university professors from various scientific disciplines, postgraduate students, and experts from ministries, public administrations, private and public enterprises, multinational corporations, associations, and similar organizations.

Building Bridges Together: Over the course of ten years since our establishment, the Association of Economists and Managers of the Balkans has established impactful partnerships with more than 1,000 diverse institutions across the Balkans region and worldwide.

LIMEN conference publications are licensed under aย Creative Commons Attribution-NonCommercial 4.0 International License.